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Poster presented at SETAC Europe's 33rd Annual Meeting held in Dublin Ireland..

This work presents and investigates a novel high-performance antenna design for remote sensing and satellite communications applications that is compact and lightweight. The performance requirements include dual-polarization, wide impedance bandwidth, low cross-polarization, high gain, and high aperture efficiency. To simultaneously achieve all these qualities is challenging and a combination of compatible performance enhancement techniques was selected and derived. A new antenna design, namely an octagonal cavity-backed radiating open prism (OCROP) antenna, was first introduced. The antenna is orthogonally and differentially fed to provide dual-polarization and low cross-polarization. The impedance bandwidth is increased by combining the resonances from the radiating feedlines and the open prism. The corner truncated octagonal ground cavity, instead of a more commonly seen square ground plane or square ground cavity, is used to further suppress the cross-polarization and enhance the gain and aperture efficiency. To show the superiority of the octagonal design, it was compared with a square ground cavity backed antenna. To further improve the gain of this novel antenna, its array and flared configurations are considered, investigated, and compared. The array design offers higher gain and aperture efficiency, while the flared design can provide lower cross-polarization. To achieve higher gain with the flared design, a larger flare angle was chosen which increased cross-polarization. To remedy the problem of the increased cross-polarization, a new iris design concept is proposed and investigated. It shows that this method can successfully suppress the cross-polarization of the flared design. This concept is general and has the potential to be applied to other types of aperture antennas. The design concepts and the simulation results are verified by fabricating and testing two prototypes, i.e., with and without a flare.

We address the question of how the approximation error/Bellman residual at each iteration of the Approximate Policy/Value Iteration algorithms influences the quality of the resulted policy. We quantify the performance loss as the Lp norm of the approximation error/Bellman residual at each iteration. Moreover, we show that the performance loss depends on the expectation of the squared Radon-Nikodym derivative of a certain distribution rather than its supremum as opposed to what has been suggested by the previous results. Also our results indicate that the contribution of the approximation/Bellman error to the performance loss is more prominent in the later iterations of API/AVI, and the effect of an error term in the earlier iterations decays exponentially fast. International audience

Genetic engineering is a promising strategy for creating agriculturally significant resistance in carrot. Several different transgenic strategies, in addition to conducting a detailed quantification of commonly used promoters to achieve disease resistance were investigated. Tissue-specific patterns and levels of protein expression were characterized in transgenic carrot plants transformed with the ?-glucuronidase gene driven by five promoters: Cauliflower moasaic virus 35S, double 35S (D35S), Arabidopsis ubiquitin (UBQ3), mannopine synthase (mas2) or rooting loci promoter (rolD). UBQ3 promoter provided the highest levels of expression in roots, while D35S and 35S promoters had high expression in leaves. rolD and Mas2 promoters had enhanced root expression; however levels were much lower compared to the constitutive promoters, which were subsequently used in this research. Genes encoding a rice peroxidase (POC1), wheat chitinase (383) and ?1,3- glucanase (638) were introduced into carrot. Lines expressing 638 alone had no enhanced resistance to B. cinerea or S. scleorotiorum, while 383 lines reduced disease symptoms by up to 40%. When 638 and 383 were co-expressed resistance levels were similar to 383 alone. High levels of disease resistance were seen in lines expressing POC1 with 70-90% reduction in symptoms to B. cinerea and S. sclerotiorum. POC1 lines had 20-30% increases in lignin levels in petioles and roots, which was enhanced with pathogen challenge. Several defence genes exhibited strong induction in POC1 expressing plants when induced with fungal cell wall elicitor. Additionally, POC1 lines had reduced H2O2 accumulation during oxidative burst response. POC1 derived resistance was effective towards necrotrophic pathogens. Over-expression of Arabidopsis Nonexpressor of Pathogenesis Related protein 1 was studied in carrot, with two independent lines successfully generated and analyzed. There was no detectable activation of the systemic acquire resistance (SAR) pathways in the absence of pathogens, however, the lines exhibited more intense and longer lasting activation of SAR when elicited with fungal cell walls or Salicylic acid. Both lines were highly resistant against biotrophic and necrotrophic foliar pathogens and the roots were resistant towards A. radicina, indicating broad-spectrum disease resistance. The results from this study demonstrate the feasibility of engineering disease resistance in carrot using several different approaches.

A search for events containing an isolated electron or muon and missing transverse momentum produced in $e^{\pm}p$ collisions is performed with the H1 and ZEUS detectors at HERA. The data were taken in the period 1994--2007 and correspond to an integrated luminosity of 0.98 fb$^{-1}$. The observed event yields are in good overall agreement with the Standard Model prediction, which is dominated by single $W$ production.In the $e^{+}p$ data, at large hadronic transverse momentum $P_{T}^{X}>25$ GeV, a total of 23 events are observed compared to a prediction of $14.0 \pm 1.9$. % The total single $W$ boson production cross section is measured as $1.06 \pm 0.16 ({\rm stat.}) \pm 0.07 ({\rm sys.})$ pb, in agreement with an SM expectation of $1.26 \pm 0.19$ pb.

Les gens consacrent une importante part de leur existence à prendre diverses décisions, pouvant affecter leur demande en transport, par exemple les choix de lieux d'habitation et de travail, les modes de transport, les heures de départ, le nombre et type de voitures dans le ménage, les itinéraires ... Les choix liés au transport sont généralement fonction du temps et caractérisés par un grand nombre de solutions alternatives qui peuvent être spatialement corrélées. Cette thèse traite de modèles pouvant être utilisés pour analyser et prédire les choix discrets dans les applications liées aux réseaux de grandes tailles. Les modèles et méthodes proposées sont particulièrement pertinents pour les applications en transport, sans toutefois s'y limiter. Nous modélisons les décisions comme des séquences de choix, dans le cadre des choix discrets dynamiques, aussi connus comme processus de décision de Markov paramétriques. Ces modèles sont réputés difficiles à estimer et à appliquer en prédiction, puisque le calcul des probabilités de choix requiert la résolution de problèmes de programmation dynamique. Nous montrons dans cette thèse qu'il est possible d'exploiter la structure du réseau et la flexibilité de la programmation dynamique afin de rendre l'approche de modélisation dynamique en choix discrets non seulement utile pour représenter les choix dépendant du temps, mais également pour modéliser plus facilement des choix statiques au sein d'ensembles de choix de très grande taille. La thèse se compose de sept articles, présentant divers modèles et méthodes d'estimation, leur application ainsi que des expériences numériques sur des modèles de choix discrets de grande taille. Nous regroupons les contributions en trois principales thématiques: modélisation du choix de route, estimation de modèles en valeur extrême multivariée (MEV) de grande taille et algorithmes d'optimisation non-linéaire. Cinq articles sont associés à la modélisation de choix de route. Nous proposons différents modèles de choix discrets dynamiques permettant aux utilités des chemins d'être corrélées, sur base de formulations MEV et logit mixte. Les modèles résultants devenant coûteux à estimer, nous présentons de nouvelles approches permettant de diminuer les efforts de calcul. Nous proposons par exemple une méthode de décomposition qui non seulement ouvre la possibilité d'estimer efficacement des modèles logit mixte, mais également d'accélérer l'estimation de modèles simples comme les modèles logit multinomiaux, ce qui a également des implications en simulation de trafic. De plus, nous comparons les règles de décision basées sur le principe de maximisation d'utilité de celles sur la minimisation du regret pour ce type de modèles. Nous proposons finalement un test statistique sur les erreurs de spécification pour les modèles de choix de route basés sur le logit multinomial. Le second thème porte sur l'estimation de modèles de choix discrets statiques avec de grands ensembles de choix. Nous établissons que certains types de modèles MEV peuvent être reformulés comme des modèles de choix discrets dynamiques, construits sur des réseaux de structure de corrélation. Ces modèles peuvent alors être estimées rapidement en utilisant des techniques de programmation dynamique en combinaison avec un algorithme efficace d'optimisation non-linéaire. La troisième et dernière thématique concerne les algorithmes d'optimisation non-linéaires dans le cadre de l'estimation de modèles complexes de choix discrets par maximum de vraisemblance. Nous examinons et adaptons des méthodes quasi-Newton structurées qui peuvent être facilement intégrées dans des algorithmes d'optimisation usuels (recherche linéaire et région de confiance) afin d'accélérer le processus d'estimation. Les modèles de choix discrets dynamiques et les méthodes d'optimisation proposés peuvent être employés dans diverses applications de choix discrets. Dans le domaine des sciences de données, des modèles qui peuvent traiter de grands ensembles de choix et des ensembles de choix séquentiels sont importants. Nos recherches peuvent dès lors être d'intérêt dans diverses applications d'analyse de la demande (analyse prédictive) ou peuvent être intégrées à des modèles d'optimisation (analyse prescriptive). De plus, nos études mettent en évidence le potentiel des techniques de programmation dynamique dans ce contexte, y compris pour des modèles statiques, ouvrant la voie à de multiples directions de recherche future. People go through their life making all kinds of decisions, and some of these decisions affect their demand for transportation, for example, their choices of where to live and where to work, how and when to travel and which route to take. Transport related choices are typically time dependent and characterized by large number of alternatives that can be spatially correlated. This thesis deals with models that can be used to analyze and predict discrete choices in large-scale networks. The proposed models and methods are highly relevant for, but not limited to, transport applications. We model decisions as sequences of choices within the dynamic discrete choice framework, also known as parametric Markov decision processes. Such models are known to be difficult to estimate and to apply to make predictions because dynamic programming problems need to be solved in order to compute choice probabilities. In this thesis we show that it is possible to explore the network structure and the flexibility of dynamic programming so that the dynamic discrete choice modeling approach is not only useful to model time dependent choices, but also makes it easier to model large-scale static choices. The thesis consists of seven articles containing a number of models and methods for estimating, applying and testing large-scale discrete choice models. In the following we group the contributions under three themes: route choice modeling, large-scale multivariate extreme value (MEV) model estimation and nonlinear optimization algorithms. Five articles are related to route choice modeling. We propose different dynamic discrete choice models that allow paths to be correlated based on the MEV and mixed logit models. The resulting route choice models become expensive to estimate and we deal with this challenge by proposing innovative methods that allow to reduce the estimation cost. For example, we propose a decomposition method that not only opens up for possibility of mixing, but also speeds up the estimation for simple logit models, which has implications also for traffic simulation. Moreover, we compare the utility maximization and regret minimization decision rules, and we propose a misspecification test for logit-based route choice models. The second theme is related to the estimation of static discrete choice models with large choice sets. We establish that a class of MEV models can be reformulated as dynamic discrete choice models on the networks of correlation structures. These dynamic models can then be estimated quickly using dynamic programming techniques and an efficient nonlinear optimization algorithm. Finally, the third theme focuses on structured quasi-Newton techniques for estimating discrete choice models by maximum likelihood. We examine and adapt switching methods that can be easily integrated into usual optimization algorithms (line search and trust region) to accelerate the estimation process. The proposed dynamic discrete choice models and estimation methods can be used in various discrete choice applications. In the area of big data analytics, models that can deal with large choice sets and sequential choices are important. Our research can therefore be of interest in various demand analysis applications (predictive analytics) or can be integrated with optimization models (prescriptive analytics). Furthermore, our studies indicate the potential of dynamic programming techniques in this context, even for static models, which opens up a variety of future research directions.

Background: Every phenotypic trait can be viewed as a “system” in which a group of interconnected componentsfunction synergistically to yield a unified whole. Once a system’s components and their interactions have beendelineated according to biological principles, we can manipulate and engineer functionally relevant components toproduce a desirable system phenotype.Results: We describe a conceptual framework for mapping quantitative trait loci (QTLs) that control complex traitsby treating trait formation as a dynamic system. This framework, called systems mapping, incorporates a system ofdifferential equations that quantifies how alterations of different components lead to the global change of traitdevelopment and function through genes, and provides a quantitative and testable platform for assessing theinterplay between gene action and development. We applied systems mapping to analyze biomass growth data ina mapping population of soybeans and identified specific loci that are responsible for the dynamics of biomasspartitioning to leaves, stem, and roots.Conclusions: We show that systems mapping implemented by design principles of biological systems is quiteversatile for deciphering the genetic machineries for size-shape, structural-functional, sink-source and pleiotropicrelationships underlying plant physiology and development. Systems mapping should enable geneticists to shedlight on the genetic complexity of any biological system in plants and other organisms and predict itsphysiological and pathological states.

La cosmologie a atteint une ère passionnante. Pour la première fois dans l’histoire humaine, un modèle quantitatif pour la formation et l’évolution de l’Univers existe,expliquant une gamme très variée de phénomènes et ayant été testé avec une impressionnante. De plus, nous sommes à l’aube d’une époque dans laquelle nous aurons à notre disposition une abondance de données de grande qualité, ce qui nous permettra d’utiliser la cosmologie comme un outil pour tester la physique fondamentale.En particulier, comme les structures de grandes échelles de l’Univers sont gouvernées par la force de gravité, la cosmologie peut être utilisée pour tester la théorie de la relativité générale d’Einstein. Cette idée a inspiré la plupart des travaux décrits dans ce manuscrit, dans lequel j’ai étudié des théories alternatives au modèle standard de la cosmologie et des tests à grandes échelles pour la relativité générale.Dans la première partie de ma thèse, je me suis concentré sur les “théories tenseur-scalaire” de la gravité. Ce sont des théories alternatives de la gravité, dans lesquelles un champ scalaire, qui est responsable de l’accélération de l’expansion de l’Univers, est ajouté à l’action de Einstein-Hilbert. Dans le deuxième chapitre, j’ai décrit le modèle de K-mouflage, une “théorie tenseur scalaire”dans laquelle le champ scalaire possède un terme cinétique non-standard, en montrant son effet non négligeable sur la dynamique des amas des galaxies. J’ai aussi montré comment cet effet peut être utilisé pour contraindre le modèle de “K-mouflage” en utilisant des observations en rayon X.En particulier, j’ai montré que le cisaillement cosmique a un pouvoir assez limité actuellement pour contraindre ces théories, à cause de la faible précision des observations actuelles et des dégénérescences avec les processus baryoniques.Dans le cinquième chapitre, j’ai donné une description de mon étude des relations de cohérence. Ce sont des relations entreles fonctions de corrélation des champs cosmiques à (n + 1) et n points, valables aussi dans le régime non-linéaire.Leur intérêt vient du fait que leur dérivation dépend seulement du Principe d’Équivalence et de l’hypothèse de conditions initiales Gaussiennes, et donc elles peuvent être utilisées pour tester ces hypothèses fondamentales du modèle standard de la cosmologie.Des relations similaires ont été étudiées auparavant, mais j’ai montré comment il est possible d’obtenir des relations qui ne s’annulent pas lorsque tous les champs sont considérés au même instant. J’ai utilisé ce résultat pour obtenir des relations de cohérence entre fonctions de corrélation de quantités observables, notamment le champ de densité des galaxies et la fluctuation de température du fond diffus cosmologie donnée par l’effet Sachs-Wolfe. Ces relations peuvent être utilisées pour des tests de la relativité générale,reposant sur des observations par satellites, sans avoir besoin de modéliser la physique des baryons aux petites échelles.Enfin, j’ai donné un aperçu des quelques perspectives possibles pour poursuivre le travail décrit dans ce manuscrit.En particulier, j’ai souligné comment des simulations numérique sont nécessaires pourmieux comprendre la formation des structuresdans le contexte des modèles “K-mouflage” et“ultra-local”. En outre, elles peuvent être aussiutilisées pour tester les hypothèses sous-tendantl’analyse des lentilles gravitationnelles faiblesprésentée dans ce manuscrit, surtout pourdistinguer l’effet de la physique des baryons etdes neutrinos de l’effet des théories de gravitémodifiée sur le cisaillement cosmique. En cequi concerne les relations de cohérence, uneétude de faisabilité de leur mesure avec les“surveys” cosmologiques est nécessaire, pourcomprendre si elles peuvent donner descontraintes compétitives sur les théoriesalternatives de la gravité. The study of physical cosmology has reached an exciting era. For the first time in human history, a quantitative model for the formation and the evolution of the Universe exists, which explains a wide range of phenomena and has been tested with incredible accuracy during the last century. Moreover, weare approaching a time when a bounty of high quality cosmological data will be available,allowing us to use cosmology as a tool to test fundamental physics.In particular, as the large-scale structures of the Universe are governed by gravity, cosmology can help us to asses the correctness of Albert Einstein’s general relativity. This idea fueledmost of the work described in this manuscript,in which we study alternative theories to the standard cosmological model and large-scale structure tests for general relativity.In particular, we focus on two scalar-tensor theories of gravity, the K-mouflage models described in Chapter 2 and the ultra-localmodels of gravity presented in Chapter 3. The K-mouflage theories are k-essence models with a non-standard kinetic term that were already studied at the linear and background levels. In this manuscript, we extend this description showing how the scalar field, which is responsible for the late time acceleration of the Universe, has a non-negligible impact on cluster dynamics, arguing that future surveysmay have the power of constraining K-mouflage models via X-ray observations. Next,we study the ultra-local models of gravity,where a scalar field with a negligible kinetic term is added to the Einstein-Hilbert action,investigating how the latter modifiescosmological structure formation and howthese models can be related to super-chameleonmodels.In Chapter 4, we present a cosmic shear data analysis in the context of f (R) and Dilaton models, and we show how current data canaccommodate most of the theories considered,once baryonic and neutrino physicsdegeneracies are taken into account. Finally, in Chapter 5 we present an analysis of consistency relations for large-scale structures,which are non-perturbative relations among correlations of cosmic fields. They are alsovalid in the non-linear regime, where very few analytical results are known, and only rely on the Equivalence Principle and primordial Gaussian initial conditions. This makes them a powerful tool to test general relativity and inflationary models using the cosmologic allarge-scale structures.We provide here the first non-vanishing equaltime consistency relations, which we use to obtain consistency relations involving observational quantities.In this Thesis manuscript, we highlight the major results of the full analysis done in the articles that are appended to the main text,where the reader can quench any thirst for technical details.

This experiment explores how changes in soundpost height affect the perceptual qualities of the violin and whether there is a threshold of change below which players and luthiers do not perceive differences. A violin installed with a height-adjustable carbon fibre soundpost was employed. The experiment was designed as a sequence of playing tests. An experimenter was present to change the soundpost height. Thirteen professional violinists and six luthiers participated. The experiment involved two phases. During the first phase, subjects played and described their feelings about the violin with different soundpost settings in order to find their optimal soundpost height. During the second phase, the experimenter randomly increased, decreased or did not change the soundpost height in ten trials within a range of approximately ±0.1 mm around their optimal height. For each trial, subjects were asked to play the violin, comparing it with the previous setting, and to decide whether they were the same or different. Initial results indicate that each subject's optimal soundpost height varies within an interquartile range of 0.3 mm and the smallest height variation that could be recognized above chance level is about 0.04 mm.